Machine Learning Engineer

Overview

The Machine Learning Engineer will have deep expertise in healthcare and pharmacy data. The focus of the role is on designing scalable, reliable, and compliant ML solutions that support improved patient outcomes, optimize pharmacy operations, and enable real-time, data-driven decision-making across the organization. ***This is a remote role, with interviews conducted onsite.* About the Role:**

• Design, build, deploy, and maintain production-grade machine learning models and pipelines using healthcare and pharmacy data (claims, EHRs, prescription data, formulary data, etc.)
• Develop robust end-to-end ML systems, including data ingestion, feature engineering, model training, validation, deployment, monitoring, and retraining
• Productionize predictive models related to medication adherence, utilization forecasting, cost optimization, and patient outcomes
• Collaborate closely with data scientists, pharmacy experts, clinicians, and engineering teams to translate business and clinical requirements into scalable ML solutions
• Implement MLOps best practices, including CI/CD for ML, model versioning, experiment tracking, performance monitoring, and automated retraining
• Optimize model performance, reliability, and latency for batch and/or real-time inference use cases
• Ensure all ML systems comply with healthcare regulations (e.g., HIPAA) and internal data governance, security, and audit requirements
• Contribute to ML architecture decisions, tooling selection, and platform improvements within the Azure ecosystem
• Document ML systems and communicate technical designs and tradeoffs clearly to both technical and non-technical stakeholders

About You

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field; or equivalent practical experience
• 3 years + of experience building and deploying machine learning systems in healthcare or pharmacy domains
• Strong proficienc...